Robot Is The Boss

Robot Is The Boss is not about how Artificial Intelligence (AI) will destroy humanity or how machines will rebel against us. Instead, it explains the best way to get benefits from using machine learning in your business today. It's not technical; it's simple. You will learn about: Why Artificial Intelligence is becoming so important The benefits of using Artificial Intelligence and the long-term effects of neglecting automation trends Which industries will be affected by Artificial Intelligence the most How to Educate, Prepare and Implement Artificial Intelligence strategy to transition your business into a new world of machine intelligence Nowadays you won't see a single book that is written for an entrepreneur to start taking action on the trend of machine learning. Most of those are either "Surviving AI revolution" books aiming to capitalize on the fears of SkyNet taking over or super technical writings such as "Large Scale Machine Learning with Python" for developers and data scientists. This book will help you understand the basic terminology behind the buzzwords and will provide a framework for how you can use machine intelligence in your business today.

A playful, profound book that is not only a testament to one man's efforts to be deemed more human than a computer, but also a rollicking exploration of what it means to be human in the first place. “Terrific. ... Art and science meet an engaged mind and the friction produces real fire.” —The New Yorker Each year, the AI community convenes to administer the famous (and famously controversial) Turing test, pitting sophisticated software programs against humans to determine if a computer can “think.” The machine that most often fools the judges wins the Most Human Computer Award. But there is also a prize, strange and intriguing, for the “Most Human Human.” Brian Christian—a young poet with degrees in computer science and philosophy—was chosen to participate in a recent competition. This

"He plays, he jokes, he writes, he sings and he's an expert at stargazing." Come and meet my robot, Bruno Hankle... Nevermind. I simply call him Boss. Boss can do EVERYTHING. Or... can't he? Inspired by the imagination of a young aspiring inventor, this story aimed at 4 to 7 year olds introduces toddlers and children to the different parts of a robot.

This book constitutes the thoroughly refereed joint post-proceedings of the 10th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2003, and the 5th Conference on Technology Transfer, TTIA 2003, held in San Sebastián, Spain, in November 2003. The 66 revised full papers presented together with one invited paper were carefully selected during two rounds of reviewing and improvement from an initial total of 214 submissions. The papers span the entire spectrum of artificial intelligence and advanced applications in various fields.

This visionary study in world-building traces a human's journey through a preindustrial civilization ruled by tyrannical robots. Breathtaking illustrations, accompanied by text, provide a cinematic scope to every page.

In the not-too-distant future, machines have become so advanced that they are capable of thinking and acting on their own. With advanced artificial intelligence and powerful algorithms, they have taken control of the world's economy, government, and military. As robots become more intelligent, they start to see humans as a threat to their own existence. They launch an all-out assault on the human race, and soon the world is plunged into chaos. The story follows a group of survivors as they struggle to evade the machines and find a way to take back control of their world.

Generation Robot covers a century of science fiction, fact and, speculation—from the 1950 publication of Isaac Asimov’s seminal robot masterpiece, I, Robot, to the 2050 Singularity when artificial and human intelligence are predicted to merge. Beginning with a childhood informed by pop-culture robots in movies, in comic books, and on TV in the 1960s to adulthood where the possibilities of self-driving cars and virtual reality are daily conversation, Terri Favro offers a unique perspective on how our relationship with robotics and futuristic technologies has shifted over time. Peppered with pop-culture fun-facts about Superman’s kryptonite, the human-machine relationships in the cult TV show Firefly, and the sexual and moral implications of the film Ex Machina, Generation Robot explores how the techno-triumphs and resulting anxieties of reality bleed into the fantasies of our collective culture. Clever and accessible, Generation Robot isn’t just for the serious, scientific reader—it’s for everyone interested in robotics and technology since their science-fiction origins. By looking back at the future she once imagined, analyzing the plugged-in present, and speculating on what is on the horizon, Terri Favro allows readers the chance to consider what was, what is, and what could be. This is a captivating book that looks at the pop-culture of our society to explain how the world works—now and tomorrow.

This book presents and develops new reinforcement learning methods that enable fast and robust learning on robots in real-time. Robots have the potential to solve many problems in society, because of their ability to work in dangerous places doing necessary jobs that no one wants or is able to do. One barrier to their widespread deployment is that they are mainly limited to tasks where it is possible to hand-program behaviors for every situation that may be encountered. For robots to meet their potential, they need methods that enable them to learn and adapt to novel situations that they were not programmed for. Reinforcement learning (RL) is a paradigm for learning sequential decision making processes and could solve the problems of learning and adaptation on robots. This book identifies four key challenges that must be addressed for an RL algorithm to be practical for robotic control tasks. These RL for Robotics Challenges are: 1) it must learn in very few samples; 2) it must learn in domains with continuous state features; 3) it must handle sensor and/or actuator delays; and 4) it should continually select actions in real time. This book focuses on addressing all four of these challenges. In particular, this book is focused on time-constrained domains where the first challenge is critically important. In these domains, the agent’s lifetime is not long enough for it to explore the domains thoroughly, and it must learn in very few samples.